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The Realities of Big Data for B2B: Very high to very negative returns

Last updated on April 14th, 2016 at 09:03 pm

Big Data is a tool most people immediately associate with the B2C channel, rather than B2B. That might be because, in the former, there are tens or hundreds of millions of customers and an exponentially larger set of data points. And that association would be wrong, according to a sampling of observers and practitioners.

Lang Smith, founder of Cloud Signalytics, a consultancy focused on the auto market, points out that all businesses collect a huge amount of data even if they believe they don’t. “It’s not data that makes anybody money, it’s the use of that data,” he cautions. “Which is very specific to each individual company.”

Over at Toronto-based systems integrator Illumiti, COO Dror Orbach scoffs at the notion that Big Data has any less utility in B2B as compared to B2C, despite an admission that Illumiti is only “getting started” with using Big Data. The company views Big Data through what’s called the Gartner model, which defines it as a combination of volume, velocity (how quickly the data builds up) and variability (the types of data you have). Orbach says it’s a challenge to make effective use of data in an enterprise resource planning system such as that managed by Illumiti because the data in the ERP is structured but elsewhere is unstructured (i.e. e-mail, social media, random notes fields, etc.)

How effective is Big Data? According to Cynthia Beath, professor emeritus at the University of Texas at Austin, and co-author for the Harvard Business Review of a 2013 study about Big Data, the answer is “that depends.” Their study looked at 51 large businesses in both the B2B and B2C category and found wide variability in terms of results. “It goes from very, very high returns to very negative returns,” she says.

This still means Big Data can be leveraged into increased efficiency that can grow revenue in a number of ways such as by increasing the number of qualified leads or avoiding unnecessary marketing expense.

Smith, says Big Data can, for example, dramatically cut down on the number of dealerships a supplier might have to target to generate a given amount of business. Because of access to Big Data, a supplier handling powertrain issues might narrow from 18,000 to 800 the number of dealerships to which it would reach out.

“So even if for some reason it only costs you a dollar to do it, that’s still $18,000 and you only need maybe a thousand. So by knowing which dealerships sell the most and deal with the most powertrain issues you are absolutely going to save an insane amount of money and maximize on your revenue.”

With now much more powerful computing ability, Orbach points to another advantage that ultimately can have a second-order impact on revenue and profitability: the ability to use data insights to support real-time decision making. At Illumiti, for example, trouble tickets from customers can be much more effectively resolved.

“As I look at the request for service the system could tell me that for the last two months we missed our service level serving this customer and so I should pay extra attention to ensuring that we do actually serve them quickly this time. That type of insight is extremely helpful in my decision making and that’s only possible if you integrate the Big Data into the real time environment and your operational systems.”

A range of observations from industry participants combine to provide a kind of best practices for how B2B firms can take advantage of Big Data. Beath says the focus has to be on how data is gathered and processed, with emphasis on elements such as using a single authorized source of data, using scorecards managed by well-trained employees and managing business rules to make sure data is accurate and believable. Lang suggests any company thinking of using Big Data sit down with a firm and be “interviewed” by that firm to break down goals and then have software tailored to that because one size does not fit all.

Of course, this costs money and the upfront expenditure—for potentially mixed results—may be daunting to many businesses, especially the smaller ones. But even that may be changing. “What you’re going to see over time is prices are going to go down as competition increases for data markets,” says David Johnson, director of product marketing at Big Data provider Oracle Eloqua. “And then it’ll be much more accessible to mid-market and up companies.”

Not everyone is convinced.

In part two of this series, we’ll look at controversial declarations that Big Data has been a failure in the B2B channel

Photo credit: Jon Evans

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Samson Okalow
Samson Okalow
Samson Okalow is a Toronto-based business writer. He has held editorial positions at a number of publications , including Canadian Business, Strategy and Adweek. He has contributed to numerous other publications including Playback, the Globe and Mail and Report on Business.